Efficient ways to impute incomplete panel data

Kristian Kleinke, Mark Stemmler, Jost Reinecke, Friedrich Lösel

Research output: Contribution to journalReview article

9 Citations (Scopus)

Abstract

We find that existing multiple imputation procedures that are currently implemented in major statistical packages and that are available to the wide majority of data analysts are limited with regard to handling incomplete panel data. We review various missing data methods that we deem useful for the analysis of incomplete panel data and discuss, how some of the shortcomings of existing procedures can be overcome. In a simulation study based on real panel data, we illustrate these procedures' quality and outline fruitful avenues of future research.

Original languageEnglish (US)
Pages (from-to)351-373
Number of pages23
JournalAStA Advances in Statistical Analysis
Volume95
Issue number4
DOIs
StatePublished - Dec 1 2011

Fingerprint

Incomplete Data
Panel Data
Statistical package
Multiple Imputation
Missing Data
Simulation Study
Panel data
simulation

All Science Journal Classification (ASJC) codes

  • Analysis
  • Statistics and Probability
  • Modeling and Simulation
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Applied Mathematics

Cite this

Kleinke, Kristian ; Stemmler, Mark ; Reinecke, Jost ; Lösel, Friedrich. / Efficient ways to impute incomplete panel data. In: AStA Advances in Statistical Analysis. 2011 ; Vol. 95, No. 4. pp. 351-373.
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Kleinke, K, Stemmler, M, Reinecke, J & Lösel, F 2011, 'Efficient ways to impute incomplete panel data', AStA Advances in Statistical Analysis, vol. 95, no. 4, pp. 351-373. https://doi.org/10.1007/s10182-011-0179-9

Efficient ways to impute incomplete panel data. / Kleinke, Kristian; Stemmler, Mark; Reinecke, Jost; Lösel, Friedrich.

In: AStA Advances in Statistical Analysis, Vol. 95, No. 4, 01.12.2011, p. 351-373.

Research output: Contribution to journalReview article

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T1 - Efficient ways to impute incomplete panel data

AU - Kleinke, Kristian

AU - Stemmler, Mark

AU - Reinecke, Jost

AU - Lösel, Friedrich

PY - 2011/12/1

Y1 - 2011/12/1

N2 - We find that existing multiple imputation procedures that are currently implemented in major statistical packages and that are available to the wide majority of data analysts are limited with regard to handling incomplete panel data. We review various missing data methods that we deem useful for the analysis of incomplete panel data and discuss, how some of the shortcomings of existing procedures can be overcome. In a simulation study based on real panel data, we illustrate these procedures' quality and outline fruitful avenues of future research.

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JO - AStA Advances in Statistical Analysis

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